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A Hybrid Heat Flux Distribution Model for Jet Impingment on a Flat Plate

[+] Author Affiliations
Gerardo Carbajal

University of Turabo, Gurabo, Puerto Rico

G. P. Peterson

University of Colorado, Boulder, CO

C. B. Sobhan

National Institute of Technology, Calicut, India

D. T. Queheillalt

University of Virginia, Charlottesville, VA

Paper No. IMECE2008-67830, pp. 875-880; 6 pages
doi:10.1115/IMECE2008-67830
From:
  • ASME 2008 International Mechanical Engineering Congress and Exposition
  • Volume 10: Heat Transfer, Fluid Flows, and Thermal Systems, Parts A, B, and C
  • Boston, Massachusetts, USA, October 31–November 6, 2008
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-4871-5 | eISBN: 978-0-7918-3840-2
  • Copyright © 2008 by ASME

abstract

A hybrid numerical-experimental technique has been developed to determine the unknown non-uniform heat flux distribution produced by the impingement of a jet on one side of a vertical flat aluminum plate. The method involves coupling of the unknown heat flux distribution as a boundary condition to the heat diffusion equation, which is solved by the finite volume method utilizing a computer code developed for the purpose. The heat flux distribution has been modeled using both a deterministic parabolic function and a probabilistic function. The resulting transient inverse problem was solved by comparing the numerical solution with the experimental data on the back side of the plate. In the experimental method, the aluminum plate was heated for 40 seconds, and an infrared camera located at the back side was used to record the transient temperature data at intervals of one second. A propane torch was the source of the impinging jet, with the flux intensity assumed to be constant with respect to time. The solid plate was cooled by natural convection and radiation heat transfer at the back side. It was found that use of the probabilistic function for the heat flux distribution produced numerical results where the temperature difference between the numerical and experimental data was within an error limit of 0.4 °C. Conversely, the parabolic function produced temperature results that did not match well with the experimental data.

Copyright © 2008 by ASME

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